Tootfinder

Why are we having fewer children?
(Interview with Berkay Ozcan, Professor at LSE)
- Couple formation happens at later age
- Women are choosing "careers" and not just "jobs"
- More people choose not to have kids at all
What else is going on? Short anser: we don't know yet
Even in countries providing a lot of support to parents, fertility rate has still declined
Immigration is no silver bullet. It's part of the solution, not th…

Berkay Ozcan: “Immigration is not a silver bullet for falling birth rates”
Berkay Ozcan discusses falling birth rates, whether immigration might provide the answer and what a smaller global population would mean for the environment.

H-Net Job Guide Weekly Report for H-NC: 4 January - 11 January https://networks.h-net.org/group/announcements/20137598/h-net-job-guide-weekly-report-h-nc-4-january-11-january

"Tree planting can combat urban heat, but some neighborhoods are falling behind"
#Trees #Environment
https://

Tree planting can combat urban heat, but some neighborhoods are falling behind
Sydney communities may be missing out on crucial tree planting projects intended to combat urban heat, leaving western and eastern parts of Greater Sydney with less protection from extreme heat, a University of Sydney-led study has revealed. In a surprising finding, the researchers found that while Greater Sydney's total tree canopy increased by 4.2% from 1.514 billion square meters to 1.578 billion square meters between 2016 and 2022, this growth was not evenly distributed.

Spagnola: Cupboard not as bare as most think https://www.dallascowboys.com/news/spagnola-cupboard-not-as-bare-as-most-think

Don Lemon pleads not guilty to two federal charges stemming from his reporting at an anti-ICE protest in a Minnesota church (CNN)
http://www.cnn.com/2026/02/13/media/don-lemon-arraignment-minnesota

Don Lemon pleads not guilty to federal charges stemming from church protest
Don Lemon pleaded not guilty Friday to federal charges following his arrest last month in connection with a protest at a church in St. Paul, Minnesota.

A citizen of Rome in 117 AD,
under Emperor Trajan,
would've found it difficult to imagine the empire not existing.
The roads, the aqueducts, the legal system, the trade networks stretching from Britain to Mesopotamia:
all of it seemed to be a near-fact of nature, like gravity
Edward Gibbon gave us six volumes explaining how that feeling turned out to be wrong,
and even he couldn't fully untangle all the causes.
But the overarching theme mig…

The empire always falls
A citizen of Rome in 117 AD, under Emperor Trajan, would've found it difficult to imagine the empire not existing. The roads, the aqueducts, the legal system, the trade networks stretching from Britain to Mesopotamia: all of it seemed to be a near-fact of nature, like gravity // the Mediterranean itself.

I would love to have seen a 15kg echidna
https://www.abc.net.au/news/2026-04-14/ice-age-giant-echidna-fossil-found-in-east-gippsland/106561526?utm_source=…

Giant echidna fossil rewrites understanding of Victoria's prehistoric past
A fossil hidden in a museum collection for 119 years has revealed giant echidnas once roamed Victoria's east, filling a major gap in Australia's prehistoric record.

So to follow up on this, I've caught it in action. Models, when quantized a bit, just do a bit more poorly with short contexts. Even going from f32 (as trained) to bf16 (as usually run) to q8 tends to do okay for "normal" context windows. And q4 you start feeling like "this model is a little stupid and gets stuck sometimes” (it is! It's just that it's still mostly careening about in the space of "plausible" most of the time. Not good guesswork, but still in the zone). With long contexts, the probability of parameters collapsing to zero are higher, so the more context the more likelihood you are to see brokenness.
And then at Q2 (2 bits per parameter) or Q1, the model falls apart completely. Parameters collapse to zero easily. You start seeing "all work and no play makes jack a dull boy” sorts of behavior, with intense and unscrutinized repetition, followed by a hard stop when it just stops working.
And quantization is a parameter that a model vendor can turn relatively easily. (they have to regenerate the model from the base with more quantization, but it's a data transformation on the order of running a terabyte through a straightforward and fast process, not like training).
If you have 1000 customers and enough equipment to handle the requests of 700, going from bf16 to q8 is a no-brainer. Suddenly you can handle the load and have a little spare capacity. They get worse results, probably pay the same per token (or they're on a subscription that hides the cost anyway so you are even freer to make trade-offs. There's a reason that subscription products are kinda poorly described.)
It's also possible for them to vary this across a day: use models during quieter periods? Maybe you get an instance running a bf16 quantization. If you use it during a high use period? You get a Q4 model.
Or intelligent routing is possible. No idea if anyone is doing this, but if they monitor what you send a bit, and you generally shoot for an expensive model for simple requests? They could totally substitute a highly quantized version of the model to answer the question.
There are •so many tricks• that can be pulled here. Some of them very reasonable to make, some of them treading into outright misleading or fraudulent, and it's weirdly hard to draw the line between them.

Spagnola: Cupboard not as bare as most think https://www.dallascowboys.com/news/spagnola-cupboard-not-as-bare-as-most-think

H-Net Job Guide Weekly Report for H-Diplo: 1-8 February
https://ift.tt/eXoI8ZW
Slave subjectivities in the Iberian Worlds (15th- 20th centuries) Date: October 31,…
via Input 4 RELCFP https:/…